Sangwon Chae

481 total citations · 1 hit paper
7 papers, 322 citations indexed

About

Sangwon Chae is a scholar working on Environmental Engineering, Computer Networks and Communications and Automotive Engineering. According to data from OpenAlex, Sangwon Chae has authored 7 papers receiving a total of 322 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Environmental Engineering, 1 paper in Computer Networks and Communications and 1 paper in Automotive Engineering. Recurrent topics in Sangwon Chae's work include Air Quality Monitoring and Forecasting (2 papers), Advanced Wireless Communication Techniques (1 paper) and Air Quality and Health Impacts (1 paper). Sangwon Chae is often cited by papers focused on Air Quality Monitoring and Forecasting (2 papers), Advanced Wireless Communication Techniques (1 paper) and Air Quality and Health Impacts (1 paper). Sangwon Chae collaborates with scholars based in South Korea. Sangwon Chae's co-authors include Sungjun Kwon, Dong-Hyun Lee, Sungwon Kang, Mingyu Kim, Hong‐Yeop Song and Suyoung Jang and has published in prestigious journals such as Scientific Reports, International Journal of Environmental Research and Public Health and Technological Forecasting and Social Change.

In The Last Decade

Sangwon Chae

6 papers receiving 309 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Predicting Infectious Disease Using Deep Learning and Big Data

2018 196 citations Sangwon Chae, Sungjun Kwon et al. International Journal of Environmental Research and Public Health profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Sangwon Chae South Korea	3	102	73	70	60	57	7	322
Gang Ai China	8	58 0.6×	49 0.7×	20 0.3×	60 1.0×	55 1.0×	21	296
Dexuan Sha United States	11	24 0.2×	59 0.8×	32 0.5×	89 1.5×	36 0.6×	24	368
Omid Hamidi Iran	10	35 0.3×	119 1.6×	19 0.3×	25 0.4×	68 1.2×	31	412
Chintan Nanda India	6	74 0.7×	21 0.3×	65 0.9×	89 1.5×	24 0.4×	7	268
Dongya Liu China	7	30 0.3×	58 0.8×	33 0.5×	67 1.1×	57 1.0×	12	304
Cafer Mert Yeşilkanat Türkiye	12	15 0.1×	131 1.8×	38 0.5×	37 0.6×	114 2.0×	41	506
Oluwole A. Odetunmibi Nigeria	14	16 0.2×	57 0.8×	26 0.4×	10 0.2×	18 0.3×	42	396
Mahdi Farnaghi Iran	11	94 0.9×	96 1.3×	100 1.4×	10 0.2×	4 0.1×	38	441
Denan Lin China	12	17 0.2×	211 2.9×	26 0.4×	12 0.2×	130 2.3×	19	534
Paulo Renato Alves Firmino Brazil	10	92 0.9×	46 0.6×	32 0.5×	14 0.2×	5 0.1×	42	326

Countries citing papers authored by Sangwon Chae

Since Specialization

Citations

This map shows the geographic impact of Sangwon Chae's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Sangwon Chae with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sangwon Chae more than expected).

Fields of papers citing papers by Sangwon Chae

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sangwon Chae. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Sangwon Chae. The network helps show where Sangwon Chae may publish in the future.

Co-authorship network of co-authors of Sangwon Chae

This figure shows the co-authorship network connecting the top 25 collaborators of Sangwon Chae. A scholar is included among the top collaborators of Sangwon Chae based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Sangwon Chae. Sangwon Chae is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

7 of 7 papers shown

1.

Chae, Sangwon, et al.. (2025). A Study of the Performance of LDPC Codes under Various Decoding Algorithms and Schedules. 300–302.

2.

Lee, Dong-Hyun, et al.. (2022). Integrated Prediction of Harmful Algal Bloom Using Cnn Deep Learning Technology. SSRN Electronic Journal. 1 indexed citations

3.

Lee, Dong-Hyun, et al.. (2022). Integrated explainable deep learning prediction of harmful algal blooms. Technological Forecasting and Social Change. 185. 122046–122046. 35 indexed citations

4.

Chae, Sangwon, et al.. (2021). PM10 and PM2.5 real-time prediction models using an interpolated convolutional neural network. Scientific Reports. 11(1). 11952–11952. 87 indexed citations

5.

Chae, Sangwon, et al.. (2020). Complex System Analysis of Korean Peninsula Earthquake Data. Scientific Reports. 10(1). 2686–2686. 1 indexed citations

6.

Chae, Sangwon, Sungjun Kwon, & Dong-Hyun Lee. (2018). Predicting Infectious Disease Using Deep Learning and Big Data. International Journal of Environmental Research and Public Health. 15(8). 1596–1596. 196 indexed citations breakdown →

7.

Chae, Sangwon, et al.. (2006). High-speed Integer Operations in the Fuzzy Consequent Part and the Defuzzification Stage for Intelligent Systems. Journal of the Institute of Electronics Engineers of Korea. 43(2). 52–62. 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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